Bidirectional effects between loneliness, smoking and alcohol use: evidence from a Mendelian randomization study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Loneliness is associated with cigarette smoking and problematic alcohol use. Observational evidence suggests these associations arise because loneliness increases substance use; however, there is potential for reverse causation (problematic drinking damages social networks, leading to loneliness). With conventional epidemiological methods, controlling for (residual) confounding and reverse causality is difficult. This study applied Mendelian randomization (MR) to assess bidirectional causal effects among loneliness, smoking behaviour and alcohol (mis)use. MR uses genetic variants as instrumental variables to estimate the causal effect of an exposure on an outcome, if the assumptions are satisfied. DESIGN: Our primary method was inverse-variance weighted (IVW) regression and the robustness of these findings was assessed with five different sensitivity methods. SETTING: European ancestry. PARTICIPANTS: Summary-level data were drawn from the largest available independent genome-wide association studies (GWAS) of loneliness (n = 511 280), smoking (initiation (n = 249 171), cigarettes per day (n = 249 171) and cessation (n = 143 852), alcoholic drinks per week (n = 226 223) and alcohol dependence (n = 46 568). MEASUREMENTS: Genetic variants predictive of the exposure variable were selected as instruments from the respective GWAS. FINDINGS: ]. We found no clear evidence for a causal effect of loneliness on drinks per week (IVW, β = 0.01, 95% CI = -0.11, 0.13, P = 0.865) or alcohol dependence (IVW, β = 0.09, 95% CI = -0.19, 0.36, P = 0.533) nor of alcohol use on loneliness (drinks per week IVW, β = 0.09, 95% CI = -0.02, 0.22, P = 0.076; alcohol dependence IVW, β = 0.06, 95% CI = -0.02, 0.13, P = 0.162). CONCLUSIONS: There appears to be tentative evidence for causal, bidirectional, increasing effects between loneliness and cigarette smoking, especially for smoking initiation increasing loneliness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".